Security Scan Report: petite-azure-x4net2xlwv-ocyg9qw65g.edgeone.app

Submitted: Feb 28, 2026, 7:30:26 PMCompleted: Feb 28, 2026, 7:31:54 PMpubliccompleted
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Summary

This website contacted 4 IPs in 2 countries across 4 domains to perform 7 HTTP transactions. The main domain is petite-azure-x4net2xlwv-ocyg9qw65g.edgeone.app and was registered NaN years ago.

Submitted URL: https://petite-azure-x4net2xlwv-ocyg9qw65g.edgeone.app/

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 90%

0
Risk Score

No malicious activity detected; appears to be a legitimate personal birthday greeting.

Safety Factors
No credential or payment collection fields
No malicious JavaScript or YARA detections
No suspicious redirects (only a single benign redirect)
Hosted on a reputable platform (edgeone.app) with no known abuse
Domain age information unavailable

Details

Page Title

Feliz Aniversário, Irmão

Scan Type

public

Language

🇵🇹

Portuguese

(80% confidence)

Category

healthcare medical

(80%)

Domain Information

Within the application-focused generic top-level domain (.app), 'petite-azure-x4net2xlwv-ocyg9qw65g.edgeone.app' is registered; it also runs on subdomain 'petite-azure-x4net2xlwv-ocyg9qw65g'. The second-level label 'edgeone' is 7 characters long holding four vowels versus 3 consonants. It segments into 2 words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://petite-azure-x4net2xlwv-ocyg9qw65g.edgeone.app/

Page Load Overview

1.84s
Total Load Time
23
HTTP Requests
10
Domains
1.0 MB
Total Size

Language Analysis

Primary Language

🇵🇹Portuguese
Code: pt
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:pt
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:pt-BR
Text Length:817 chars
Detector Agreement:100%

Website Classification

Primary Category

healthcare medical80% confidence
Type: static
Method: ml+structural

All Detected Categories

healthcare medical
80%
adult content
78%
education learning
53%
entertainment media
47%
government public service
45%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8142.250.186.42United States
5142.250.201.78United States
543.152.26.58Singapore
5142.251.141.131United StatesUnknown
234--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A7A1B823EB564017A013D3A037D7A31E727C91071A4DC5E97EDD63A8AFC12B58493B9C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:/RUffGMXUkXUVNHrD3jDyF369F18j5psrHA2uoSUr295BAfI:/RUffGMEeUVNHrD3jD6369F18j5psrHe

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:4705:CAAgCgQAMAhNsJAIigAQBYOMBDGEAeiAAZIAKBgIQAIVRgBAIgMYUqAOIACIAABBIgAUYCHQARABQBQAQHCAiiABEBwhAAGG

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:7e7e187c30400003
Perceptual Hash:c8d4ab54ab54295f
Difference Hash:ccc0b0f060900003
Wavelet Hash:fefe78fc38408083
Color Hash:#86802d

Other Hashes

Crop Resistant:ccc0b0f060900003

Scan History

Scan history not available

Unable to load historical scan data